{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.datasets.samples_generator import make_blobs\n",
    "# 生成数据\n",
    "centers = [[-2, 2], [2, 2], [0, 4]]\n",
    "X, y = make_blobs(n_samples=60, centers=centers, random_state=0, cluster_std=0.60)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 576.0,
       "width": 923.0
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 画出数据\n",
    "plt.figure(figsize=(16, 10))\n",
    "c = np.array(centers)\n",
    "plt.scatter(X[:, 0], X[:, 1], c=y, s=100, cmap='cool');         # 画出样本\n",
    "plt.scatter(c[:, 0], c[:, 1], s=100, marker='^', c='orange');   # 画出中心点"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "# 模型训练\n",
    "k = 5\n",
    "clf = KNeighborsClassifier(n_neighbors=k)\n",
    "clf.fit(X, y);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 进行预测\n",
    "X_sample = [0, 2]\n",
    "X_sample = np.array(X_sample).reshape(1, -1)\n",
    "y_sample = clf.predict(X_sample);\n",
    "neighbors = clf.kneighbors(X_sample, return_distance=False);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1152x720 with 0 Axes>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x117c80f60>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x117c89588>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x117c89358>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x117c89ba8>]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x117c89d68>]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x117c89550>]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x117c89fd0>]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x117c96550>]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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0xi0rNm/pe9+rN71p8oEIgCEpNwFgBbig+rnq6Oqt1fc2cc951RuqQ6unNdnVCTBNX6leXf1y9ejqUdUzqz+pvtTkQxkAwPgMuWvzZt+bQiaweFdfVX/7t7V27cLW33DDZP0Prh52LmC2KTcBYOQ+VD24+n9bseZ91SHVp6YyETDrPlod12T3+H+q/r7Jf29Oq95T/ZfqyI3XPy7TjADAwqy7qa64YvjcS3z6Eu5y5jfUyScvvNi82Q03THLmfboRGIhnbgLAiP2/6heqmxaw9qomuz1PqR455FDAzFpbvaTJLvEtcXr11OrfVK+vdp3SXADAcH784zt+/drrLut7F3y6Cy44rR9ec0HP/KX3bFHuYssThnXddfXls+q7350Uz9dfX3Nztfvutc8+9YAH1AMOrlWrlntSpulr59T55w+Tdd559fVz6kGHDJMHzDblJgCM1KVNCoGFFJs3u756VpOjI3cbYqgtcEl1UpMjKf+5urFJofGwJiXrk6vtl2gWYDg3NPn5+7EFrP376ptNPmyx+5BDAQCD2+YWZdb8/HxXX/2dbrjhqvbb78i+8IW/6p8+9OJ22mnPDjjguA444FFtmN/QNnN3fnjcNs6Xu0v48do65ZQ688xav/72r19++eQ6++zaZZf66Z+uQw+bFJ+sPF/8wsB5X1RuAsNQbgLASJ3YZPflYn2vyRGRrx0g646cV728em+1bhOvn7Lx657Vi6rfqXaY8kzAcH69hRWbNzu9yfM4P1z5szEAuOvaYYf61rfe25lnvasLLjita6+9pIMP/sWOf9Y/dPADf7EDD/zZ9tjj/s1tZdt197tPaWC22Pe/X+95d11zzZbdf+21k6NGv/71etrTJ/9usHJc88Phn697/vn1ox/VmjXD5gKzx2eiAGCEzm3y3Lqh/O/q8gHzbutN1UOqd7bpYvOWrqj+oDqsOnOKMwHDeW+T3ZeL9ZG2/EhbAGD6rr/++j7+8Y/3ile8osc//vH9+Z//eXNztc02l7Rml317ws/9r1760gs7/ln/UNWua/Ztzz0fsNXFZtU++w49PVvjexfU2/5my4vNW/rWt+rtb5vs+mTluOii6eRePKVcYLYoNwFghN5czQ+Yd2P1tgHzbukPq+dW123lum9Uj64+PfhEwJDWV789YN5/bXLELQCw9K644opOOumkLti4Xevoo4/uSU96UqeeempHH310j3nMY6o68cQX94Qn/EWHHPJL7bpmmFbygQ8cJIYFuO7aeuc766ZFPPPkoosmuzhZOS6/Yly5wGxxLC0AjNAnp5D5qeplA2e+o/q9Ray/tskz/M6u9h9kImBoH25y7PRQrmqyM/05A2YCALc3Pz/5uOTatWs78cQTO+200/rGN77RHnvs0Vve8pYOOOCATj755Pbdd9+22267W619yEPrIx+pG28cZpa996573WuYLLbehz5U11+/+Jxzzqmvfa0O8UzFFWH9nR27tEDrppQLzBY7NwFgZOabznGtQ2f+/+zdeVyU9f7//8eAIKAogqKyuO+KC6CCgrmWdZJK0yxttSzN0vJ8Wn9lR491/JZtdk52rDTLsmOmZVamdlJQUBZT0wzFDQZwQUBUFGTm98folB0XlmsYluf9dpsbMlzXkxemOXO9rvfrnQlMMSAnD3gQY1eqiohxVjogc4UDMkVERGq7kpIStm3bxrx58xgzZgyBgYEcPHgQDw8P6taty/Tp0/n11185duwYI0aMAKBVq1b/09gEqFsXBg02rrbrr4dyTLIVAxw9amtIGmXDT2DVm7ca4TJ/9Q1R10G5IlK7aOWmiIhINVNE2Ue8lkaOwXkvY2tMGuEHYD0w1KC8sioEvgW2AL8AZwBPoDPQB9vq0vpOqk3E2ZIckJnsgEwREZHa5syZM2zdupXdu3czefJkfv75Z3r37k2PHj2Ijo7mzTffpHHjxphMJt55550y5/ftA7/tgYMHK1Znnz7Quk3FMqT8kgx+MXfsGBw+BC1bGZsrlc+/afXKFZHaRc1NERGRasa1GuSewvg9PP9F5Tc3TwGzgX9jG5X5Z99f+OgN3A/MAHwrpzSRKmN/WQ6OjbXNKfO9+t+UdKAYcKtAXSIiIrVNUVER7u7urF27lhdffJHk5GRcXV2JjIzkoYceomfPnuTm5tKwYUNDvp/JBcaMgcWLITu7fBmdO8MNNxhSjpRT2j4HZKapuVkTBATYVlQbuRLXZIKA5sbliUjtpbG0IiIi1UwdwBHb0bQ2MOu/QIGBeWBbOVlscObVxAEhwD+4fGPzjwqAt4Fu/N7wFKktSr1lTnEx3HYb+PlBx45w332wZUvFc0VERGqpw4cP8/HHHzNx4kS6dOnCkCFDAGjSpAkjR45k48aN5Ofn8+OPP+Lm5oarq6thjc2LPL3g3vsgJKRs55lMEBUNt98OLo66e1Ou6dxZOHGtNzvlkJVlfKZUPi8v28t2I3XuDB6exmaKSO2klZsiIiLVUDiQYXBmmIFZjhgpeQ7YBfR0QPafrQZGYhsBXBZZwF+Aj4G7jC5KpIrypZSjst3cbJs67dkD8fG2R2Gh7WsjR0J+PkREQGQkHhEReDRu7MCqRUREqpeSkhJ27txJXFwcwcHB3HLLLbz++ut8/fXXREVFMW3aNKKjowHo2bMnPXtWxqtmGw8PGDnKNpwhNhbM5qsf3749DBwIAYGVUp5cxalTjsktMPpOV3Gavn1tL9+N0qevcVkiUrupuSkiIlINjQBWOiDTKGUaU1kGaTi+ubkTuJ2yNzYvsgD3AC2B/kYVJVKF9cQ2RrZUXFygSxfbY8KE35+fOhU2bICEBHj3XRqMHo3pvfdYs2YNaWlpREZGEhISQp06evsiIiK1Q2FhIRaLhXr16vHwww+zdOlSCgoK6N69O5MmTQLg1Vdf5c0333Rypb/r2Mn2yM6y7cOZlQWnL9wB1bAhNA+Atm2hUSOnlil/YOC00UtzHRUsla5Va+jRA7Zvr3hWz17QsqXtz8eJHMjMhJwcKLGAR11o2gwCA2wrwkVErkVXB0RERKqhscB0IM+gvGDgZoOyAEoMzPojR4+pLAbuA85WMKfkQs52QO/LpKaLBlZVNOS662wPAIuFO8+cASA9PZ333nuPxx57DA8PD0aMGGG/uFtYWIi/v39Fv7OIiEiVUFJSwrfffktsbCxxcXEkJSXx1ltvMWnSJIYNG8att95Kv379Lhkr6+ZWNXenbtbc9pCqr349x+R6ezsmV5zjhuGQkWFrRJZX48YwdCgkJUJiom2gy+W4uNhG1/aNgODg8n8/Ean5tOemiIhINeQFzDQw7xWMvePJ18CsP/JzUO5FnwIpBmXtA+YblCVSld0DGHpp1cWFyfXrA/Dggw+yfft28vLyWLVqFaNHjwbg66+/pmnTprRp04Zx48Yxb948zp6t6G0JIiIilcNqtXLw4EE++eQTHnnkETIzM3FxceGvf/0re/bs4dZbb2XDhg088MADANx+++3ceOONhu+XKeLh6ZiVtM3V3K5RPD3hnntsDcryaNIEhg+HjxfD6tVXbmwCWCywaxd8+IHt2KJz5fueIlLzaeWmiIhINfUosBzYUMGc2zB+f0hHjY7t5aDci/5lcN67wDR0N5nUbE2xNTg/MCjvFqDDn57z9vZm8ODB9s/vuusu+vTpQ3x8PAkJCSxdupTJkydz/PhxbrvtNiIiIoiMjCQiIoKAgACDKhMRESmfkpIS9u3bR8eOHdm3bx8DBw7EbDbTsmVLoqKiKCwsxGQysWfPHkwmk7PLlVqmTRtITjY2s3UbY/PE+Ro0hAcfgrU/lO3PS3hvaN0KPvsMSso44ikpEcwZMP5u8NJIJBH5E5O1ig9BN5lMyaGhoaHJRv8rKyIiUgPkAIOBHeU8vx+wBqhvWEU2qUBHgzM7A7sNzvyjLMARLZAdQIgDckWqklygK7a/RxXRENgFBJbz/JycHBYsWEB8fDzx8fEcO3aMjRs3Eh0dzWeffUbbtm3p2bMn7u7uFaxURETk6vbv38/SpUuJi4tj8+bNnD59mtzcXNzd3Vm+fDlRUVEEa+aiVAHZWfDee8bl+fnBo4+CSXd41liZZti61bbC8vxl9o6pUwe6dYPefWwNzY8Wlb2x+UeBgXD//eCqZVoi1VZYWBgpKSkpVqs1zKhM/S9BRESkGvMDfgIeAFaW8dzx2MamOmKblQ7AdVR8VekfTTQw63KSHJSbjJqbUvM1ApYC1wPlnRzlCiym/I1NAD8/P5555hnANvLvwIEDBAQEYLVaeeedd9i6dSuurq6EhYXxzDPPMGLECAoLC/H09KzAdxURkdruxIkTbN68mdjYWAoLC3n77bfZv38/3333HdHR0UyZMoV+/fpR/8LY9TvvvNPJFYv8rllz6NgRfvvNmLzoAWps1nQBgXDrbTBiBBw9Zhsze74Y6riBvz/4N7E1IouLYP78ijU2Acxm2BgLgwYZU7+I1AxqboqIiFRzjYAvgc+BWVx7dWMv4G/ACAfX9RTGNTcbA/cZlHUladUsV6SqGQCsBkYCJ8t4rifwCRBjYD0mk4k2bX6fibZp0ybOnDlDcnIy8fHx+PnZdvEdNWoUO3futI+yHTRoEL16OXoItoiIVGeHDx/mzJkzdOrUiZkzZzJjxgx8fHyIiopi6NChAAwdOtT+a5Gq7i9/gUOHoKJbmHfoAN27G1OTVH2udWz7q15pj9VNm+HECWO+V+xG6NnTMXvEikj1pOamiIhIDWACxgJ3ALHAemwrBrMvfC0QCMO2qqrPhecc7SZse3l+akDWPwEfA3Ku5jLTdKp0rkhVNATbWNmJwHelPCcK+BBo76ii/sDLy4vo6Giio6Ptz82fP5/NmzeTkJDA559/TmpqKvPnz+fLL79k48aN9r07W7RooX3QRERqsU8//ZRvvvmGuLg40tPTmTBhAu+//z533nknI0eOpEuXLri4aLmaVE/eDWD0GPh0SflX2fn7w623gl4uCdj+HCUbOB7JarXlDR1mXKaIVG9qboqIiNQgJmyrpwY4u5AL3sG25+QvFch4FBhjTDlX5agbQHVjqdQ2QdhWcG4B/gX8ABz50zF+2Bqhk7CNsHbmNbAWLVrQokULxo4dC9jG2QJ4enpiNpuZPn06ZrOZnj17sm3bNk6cOMHu3bsJCwvTOFsRkRro7NmzJCUlERcXR2xsLOPHj+fOO+9k165d+Pj4MGfOHPr370+LFi0AaN++Mm7PEXG8Nm1g/Hj44gs4fbps57ZsCWPGgKeXY2qT6ufAATh1ytjMHTvU3BSR36m5KSIiIg7TCNsq0puBxHKcPw2Ya2hFV9bTQbkabim1kQmIuPCwApmA+cKvmwEtcG5D82ours688cYbufHGGwFIT0/n0KFDACQmJhITE4PFYqFnz55EREQwc+ZMGjVqhNVq1epOEZFqJjc3l82bN9OvXz98fHxo1aoVubm59O7dm+joaDp37gzA7NmznVypiOO1ag2TJ8OaNbBzp2213NV4eMDAgdCnj/bZlEuZzcZnFhTYHt7exmeLSPWj5qaIiIg4lD+wCXgZmA0Ul+KcQODf2EbbVpYQoAFl3yvwatyAcAPzRKqji6OxA51dSAUEBwcTHBwMwA033MDJkyfZtm0bCQkJbN26lXr16pGXl0fnzp3p27evfZRtnz59tLpTRKQKOn78OC+++CKxsbH88ssv+Pj48M0339C/f3/Wr19P27Zt8fDwcHaZIk7hVQ9uGwmDB8O2bba9OLOy4Nw529cbNrTtsdihI3TrBm5uzq1XqqbjxxyTe+yompsiYqPmpoiIiDicGzAD2z587wP/AXYDlj8c4wX0BR4Abgcq+3KSO3APtlG6RhmNxtKK1ER169YlIiKCiIgI+3MlJSW88847JCQksGrVKmbMmMHXX3/N9ddfz+uvv46/vz8RERG0bdtWqztFRCqJxWJh9+7dxMbGEhcXR0JCAjt27KB+/frk5+czadIkoqOj6dq1q32/zK5duzq5apGqoaEPDBz0++eWEtt+mlqhKaVRXJq7msuTe94xuSJS/ai5KSIiIpWmOfDChccZIA04h23FZFvA1XmlAfA4thWjRQZkmYAnDMgRkerB09OTUaNGMWrUKACKiorsTcxdu3Yxb948Dh48SOPGjZk9ezYTJ04kPT2dRo0aUb9+fWeWLiJSY5w7d46kpCTS09MZO3Ysq1evJiYmhm7duhEVFcXMmTMxmUx4eHiwZMkSZ5crUq24OPvNmlQrjlrR666VwiJygZqbIiIi4hRe2EbBViXtsa0wfd6ArCfRSFqR2szd3d3+6w8++ACA7OxsEhISaNmyJQBPPPEEK1asICQkhMjISIYPH84tt9zilHpFRKoji8WCi4sLK1eu5PXXX2fr1q1YLBYGDx7M2LFjGTZsGDk5Ofj6+jq7VBGRWsXfv3rlikj1o0ECIiIiIn/wFHBjBTP6A7MMqEVEapZmzZpx66230qtXLwA+++wzEhMTeeihhygoKGDTpk0AfPrpp/zlL3/h73//O+vWrePkSSN3AxYRqb7MZjOfffYZjz76KN27d+euu+4CwNvbm+HDh7N27Vry8/P5/vvvAfDw8FBjU0TECQIDjc9s2BDqaeCJiFxgslqtzq7hqkwmU3JoaGhocnKys0sRERGRWqIQuBP4qhznDgJWYhu1KyJSHtu2bWPZsmXEx8ezdetWvLy8OHr0KMePH2fVqlVERkbSsWNH+/5wIiI1kcVi4ddffyUuLo6uXbsSFRXFmDFj2Lx5M9HR0URFRTFo0CC6dOni7FJFRORPLCXw1ltg5D16AwbAoMHG5YlI5QkLCyMlJSXFarWGGZWpsbQiIiIif+IJrAAWAH8FCkpxjgfwd2Aazt87VESqt169etlXd54/f57Dhw9jMpk4ePAgc+bMITU1FR8fH/r27csHH3xAYGAgp06d0t6dIlKtnTt3DpPJhLu7O3fddRfff/89ubm5dOnShWeffZaoqCgWLVqEp6enfU9jERGpmlxcoXdvWL/emDxXVwg1rCUiIjWBmpsiIiIil2ECJgK3Ax9deOwELH86pjMwHpgAaPsPETFanTp1aNOmDQC9e/fmt99+Iycnhy1bthAfH4+fnx8FBQX4+vrSoUMHIiIiiIyM5KabbiIgIMDJ1YuIXFlRURE//vgjsbGxxMXFsXXrVv7zn/8wYsQIBg4cyJ133km/fv3w8/Ozn+Pl5eXEikVEpCwiImHHDjh2rOJZ1w20jaUVEblIY2lFRERESukMsOfCRw+gI+Dt1IpERGyjG3ft2kV8fDwJCQnEx8czd+5cbrrpJp566ik8PDyIiIggIiJCe8+JiNOYzWZiY2PZtGkTr776KufPn6dly5b06dOHqKgooqKi6NOnD56ens4uVUREDJKVCQsXQnFx+TNatoR77rGtBhWR6kljaUVEREScyAsIdXYRIiJ/4uLiQkhICCEhIUycOPGSrzVu3Jj169fz9ttvk5+fzwsvvMDMmTPZsWMHVquVbt264eqqK0UiYiyr1YrZbCYoKIjExETGjBnDwYMHCQgIIDo6mry8PJo1a8axY8e0f7CISA3WPADuvAs++7R8Dc4WLWDsnWpsisj/0spNERGRcrACm4DNwHYgH3ADOgDhwA1AA6dVJyIicimLxcKePXtwc3Ojffv2PPHEE7z11lvUq1ePPn36cPPNN/PEE09gtVq1l52IlEtqaipfffUVcXFxbNq0CYvFwvHjx8nNzeXbb78lKiqKVq1a6f8xIiK10PHj8NVKyMgo3fEmE/TrDwMHQh0tzxKp9hyxclPNTRERkTKwAAuA14HUqxxXD7gbmAE0q4S6REREyio/P5+tW7cSHx+Pu7s7zzzzDIsWLWL27NlERkba9+/s0aOHVlaJyCVOnjxJfHw8sbGxeHl58dxzz7F48WLeffddoqKiiI6Opl+/fjRu3NjZpYqISBVhscAvv0BSIqSnX/6YOnUgpDv07QNNdTFFpMZQc1NERMSJDgD3MprfkgAAIABJREFUAHFlOMcX+Bdwh0MqEhERMVZGRgbr1q2z7995+PBhjh8/zokTJ5g7dy6RkZFERkbi7+/v7FJFpBJlZmZSUlJCcHAwTzzxBG+//Tb16tWjX79+3HLLLUyaNMnZJYqISDVSUGDbjzMnB0pKwMPD1sxs1hTc3J1dnYgYTc1NERERJ9kNDAaOlPP8ucCTxpUjIiJSKc6ePYuHhwd79+7liSeeICEhgZycHNq0acPq1avp1KkTu3fvpn379ri5uTm7XBEx0OLFi1m/fj2xsbEcOHCAp556ijlz5pCSkoLJZCIkJIQ6mhUoIiIiItfgiOamXoWKiIhcwwlse2iWt7EJMB0IAsYYUpFIxV28vU27XonI1Xh4eADQvn17vvnmG6xWK/v27SM+Pp4WLVpQVFREWJjt/Wl4eDiRkZHcfffdhISEOLNsESmDoqIitm3bRlxcHLGxsUybNo2BAwfy3//+F3d3d1566SWioqJo3bo1AKGhoU6uWERERByh8Axs3w4HDkBWFpw6ZXu+QQMICIC27SCkG7jXdW6dIqDmpoiIyDVNBUq55/1VTQauA5oakCVSVoXAf4DVQBJwCNseso2BXtj+bN4PBDirQBGpFkwmE+3bt6d9+/b2544dO0ZSUpJ9lK3ZbCYkJIQHHniAM2fO2EfZ9uzZE3d3zRkTcbaCggLi4+MZOHAgJSUl+Pv7c/bsWcLCwoiKiqJJkyYALFy40MmVioiISGUoLoL//gSJW+H8+f/9en6+7fHrr7D2B+jf3/Zwca30UkXsNJZWRETkKpKBcAPzpgDzDMwTuRYL8E/gJWyrkK/GFbgXeA1o5NiyRKQW+PLLL/nxxx9JSEjg559/5oEHHuDf//43cXFxZGdnExkZSWBgoLPLFKkV0tPTee2114iLi+Pnn3/Gy8uLxMREOnXqxJYtWwgJCcHLy8vZZYqIiEglO3oUPl8KJ651weBPmjeHO8ZCw4aOqUtqFkeMpXUxKkhERKQm+pfBeR8BBQZnilzJcWx7xT7OtRubACXAh0A3YJMD6xKR2mHkyJG88847JCUlcfLkSWbNmgVAYmIiU6ZMISgoiODgYB599FHAtr/n2bNnnVmySLVntVr57bffeP/997nvvvvo27cvVqsVk8lEZmYm99xzD4mJieTm5tKpUycA+vbtq8amiIhILXT0KCxaWPbGJtjG1i78EE7mG1+XSGmouSkiInIFVuBLgzMLgHUGZ4pcTg4wCNhQjnMzgWFArKEViUht5uXlRdOmtsHsTzzxBFlZWRw4cIBXX33Vvn/f8uXLadiwIREREUybNo3PP/+coqIiZ5YtUuUVFxezdetW1qxZA8D7779Pp06deO2116hTpw6TJ0/m/PnzBAUFsWzZMqZOnUpoaCh16miXIhERkdqsqAiWfgaFheXPyM+H//wHLCXG1SVSWhpLKyIicgX7gPbXPKrsngf+7oBckYuswAhs+2tWhB+wG/CvcEUiItd29uxZUlJSiI+PJz4+nh07drB7925OnjzJxIkTiYiIIDIyktDQUDw9PZ1drohTXFyF+emnn/L++++zZcsWzp07x2233cayZcvIy8ujqKgIf3/96y0iIiJX9t13sHWLMVlDh9n24BS5Eo2lFRERqUR7q1muyEUfU/HGJthWfz5qQI6ISGl4eHjQr18/pk+fzhdffEFqaip16tShqKiI4OBgli9fzuDBg2nQoAFbttiuxKxZs4YDBw5Q1W/aFSmv7Oxsli9fzrRp0wgPD+fpp58GwNXVlYEDB7Jq1Sry8/NZtmwZAD4+PmpsioiIyFWdOgVJicblbYqD4mLj8kRKQ3NIRERErsBRr8s0YE8cyQLMNDDvC2yrN7sYmCkiUhbNmjXjjTfeAODcuXNs27aNbt26YbFYeOyxx9i7dy9NmzYlIiKCxx57jCFDhthXt4lUJ1arlb179xIbG0tERARdu3Zl5MiRpKWlER0dzfjx47n++usBuOOOO5xcrYiIiFRX21LAYjEur7AQdu+GHj2MyxS5FjU3RURErsCnmuWKgG1P1zSDM+cDbxucKSJSHnXr1iUiIsL+eWpqKmazmYSEBBISEuwNzZEjR3Lo0CEiIyOJjIwkKiqKVq1aOalqkcs7f/48Li4uWCwW7rjjDmJjYzl27BgdOnTg1VdfpWvXrqxevRofHx8160VERMQw+/cbn3lgv5qbUrnU3BQREbmC7g7K7emgXBGwNTerQ6aIiFECAwMZNWoUo0aNsj83Y8YMNm7cSHx8PC+88AIDBgzgo48+4vvvvyclJYXIyEh69+5N/fr1nVi51DZnz54lLi7O/khISCA2NpZevXoRFhbGuHHj6N+/P02bNrWf06hRIydWLCIilc1SAqdOg9UCnp7gXtfZFUlNY7VCVpbxuZmZxmeKXI2amyIiIlfgA3QFdhmc28/gPJE/SnZA5h7gFKAWgIhUFz179qRnz548/vjjABQV2YbCnzx5ku+//56///3vnDt3jkGDBrFu3TpOnjxJVlYWHTp00Ao5McyRI0fYtGkTKSkpzJo1i8zMTG655Rb7auJnn32WTp06AfDcc885uVoRkd8VF4E509YAKSgAE+DtDc0DICAA3NycXWHNcuqUbUxoaipkZ8P5879/zc8PWrSE8DAICHRejVJznC+Gc+eMzy0oMD5T5GrU3BQREbmKCcCTBuZ1B8INzBP5M0fcLGkFjqDmpohUX+7u7gCMGTOGMWPGUFxczI4dO8i8cIv5hg0biImJwdfXl4iICCIjI5k6dSre3t7OLFuqEavVSk5ODo0bN2bdunVMnjyZvXv30qRJE6Kjozlz5gytW7cmLy8PN3UFRKSKysuD+M2wffuVmx8eHtCzJ0RGQoOGlVtfTXO+GH7aYPs9v9L+hzk5tse2FGjdGkaMgEa+lVuniEhVZLJarc6u4apMJlNyaGhoaHKyI9YhiIiIXF0u0PbCRyMsAu41KEvkcroAvzogNw1o44BcEZGq4ujRo/a9OxMTE1m9ejVnz54lOjqavn37EhkZSUREBB07dsTFxcXZ5UoVsGfPHr7//ntiY2OJi4vDz8+P3bt3s3//fn766SeioqJo3769VgOLSJVntUJSIqxdC8XFpTvH3R1uuAF6hYL+N1d2eXnw6RI4dqxs57m5wS23QteujqlLaj6rFeb8w/jVm02awORHjc2UmiMsLIyUlJQUq9UaZlSmVm6KiIhcRSNgHjDegKyhwD0G5IhcTQDGNzdNgL/BmSIiVY2/vz8xMTHExMTYnzt37hyPPPIICQkJvPLKK+zdu5fvvvuO4cOHs3DhQgICAujbty8+Pj5OrFwqw+nTp9myZQtxcXEEBgYyYcIEvvjiC1auXEl0dDT/+te/6N+/PwBt2rShTRvdEiQi1YPVAqu+sa0MLIuiIli1CrKPwI03qsFZFifzYdFCyM8v+7nFxfDFMluDqls342uTms9kgubN4eBBY3MDAozNE7kW3W4qIiJyDXcBD1QwIxhYiK1JJOJIoQ7I7IRG0opI7eTt7c2kSZP46KOPSE1N5dixYwwcOBCAlStXcvvtt+Pr60vXrl1ZsmQJALm5uViuNFtOqo2jR49y/PhxAO6//34aNmzIiBEj2LBhg30l5vPPP09SUhJvvPEGo0aNolmzZs4sWUSkXNatK3tj848St8JPPxlWTo1ntcDy5eVrbP7RVyvhRI4xNUnt44h7sFrrvi6pZGpuioiIXIMJeA/b/pvl0Qb4EQgyrCKRK7veAZnDHJApIlIdNW7cGA8PDwC++uor8vLy+Pnnn5k6dSqtW7cG4MEHH6RRo0Zcf/31vPjii2zcuNGZJUspWa1WFi1axIMPPkjHjh1p2rQpixYtAuDee+9l8+bN5OXlsX79eh54wHbbm8bNikh1d/AgbN5c8ZzYjZCRXvGc2iAxCQ4frnjO+fPw9de2FZwiZdUrFIzcZcHTE7p2MS5PpDQ0llZERKQU6gALsI2WnQKU9gbJicCrQAMH1SXyZ4OB9sBeAzMnGZglIlKTuLq60r17d7p3725/bsGCBWzdupX4+Hji4+M5evQoAwYMYMWKFXz11VdERkYSGRlJ165dcXV1dWL1tdf58+fZvn07cXFxxMXFMXPmTDp37sySJUsIDAzk//7v/4iOjqZDhw4A9tW6IiI1idUK3642MOtbeGiixtNejcUCm+KMyzt0yNZUDm5hXKbUDvXrQ3hv2LrFmLz+UVDHzZgskdLSyk0REZFSMgFjgTTgbaAHlx8z6w9MBnZiW/FZnRubJ0+e5J///CcFBQXOLkVKyQWYYWDeHdjG0oqISOn4+voyfPhw/va3v/HDDz8wf/58wLbqs06dOsybN4+ePXvSunVrrFYrubm5rF692j4CtSr5YVc2FkvFloRYLFZ+2JVtUEXlc+bMGWJjYwHIyMigUaNG9OnTh8WLFxMQEIC7uzsAa9euvWT1plZmikhNdvAAHDtmXF5WFpgzjMurifbtg5Mnjc1MSjI2zyi6llD1DRkCjRpVPCcwECIjKp4jUlZauSkiIlJGDYHHLjxOYWti5gNuQAds42dryqWwadOmsXDhQpKTk/nwww+dXY6U0l3A58CqCuY0AeZVvBwREQGio6OJjo4GID8/n3379mEymdi9ezfjx48nLy+P9u3bExERwauvvkrTpk2xWCy4GDkzrAzeWJvKW+v3MjosiDmjuuPiUvZXNxaLlaeX72BZcgZTh7TniWEdHFDp5e3du5f33nuP2NhYUlJScHNz4/DhwwQGBrJixQr69u2Lt7d3pdUjIlLV7PzF+MwdOyEo2PjcmuLgQeMzDx0yPtMIupZQ9bm7w9g7YdFCKCwsX0bDhjB6DLhoGIk4gVZuioiIVEB9IBIYDgwBgqk5jc20tDQWL14MwOLFi0lLS3NyRVJaJuAjoPu1DryKesBKbA1OERExVsOGDQkLCwOgf//+5OTk8Ouvv/Lss8/i6elJgwYNOH36NL6+vgwcOJBnn32Wr776itzc3Eqp74dd2by13jbgfFlyBk8v31HmFZx/bGwCvLV+r0NWcFqtVtLS0vjoo4946KGHGDVqFAAFBQWkpaUxZswY4uLiyMvLo3HjxphMJoYOHarGpojUeplm4zOzMo3PrEmys4zPzM+HM6eNz60IXUuoPvz94b77wNe37Oc2bw73P2BrcIo4g5qbIiIiclmzZ8+mpKQEgJKSEmbPnu3kiqQsGgH/xdZ0L6sgYB3Qz9CKRETkSlxcXOjUqRP3338/7733Hp6enri7u7N8+XKGDRvGzp07mTBhgn206j/+8Q/eeecdkpOTKS4uNryeoZ2bMjosyP55WRucf25sAowOC2Jo56YVrq2kpIRt27aRkJAAwMsvv0y7du2YOXMmRUVF3HTTTQCEhoayYsUKpk+fTt++fe2jZ0VExLZHppEjaS9yRGZNctpBTcjTZxyTW166llC9+DeFRx6ByEioU4o5n3XrwuDBMOFBNTbFuUxWa8X2z3A0k8mUHBoaGpqcnOzsUkRERGqNtLQ0OnbsaH9DAuDq6spvv/1G27ZtnViZlJUF296vM4BrXWtwAx4A5mAbvywiIlWH1WrFYrHg6urK008/zQ8//MCOHTuoW7cuL730Ek899RRpaWl4eXnRvHnzCn+/KzUorzWitrznXcuHH37I559/Tnx8PKdPn+aBBx5gwYIFZGVlYbFYCAwMLHe2iEhtY7HArJnG57q4wAsvGp9bU8x/F44cMT53yhTwa2x8bnnoWkL1VngGtm+HAwds++ieOmV7vkEDCAiAtm0hJATc6zq3Tql+wsLCSElJSbFarWFGZVZ4z02TyeQH3Ab8BQgBAoEibFuQLQQWWq1WS0W/j4iIiFSeP95pedHFOy61X0b14gJMwta0XA58AyQDh4ASoDEQClwH3AtUfE2NiIg4gslkwtXVtqHRnDlzmDNnDqdOnSIpKYlGjRoBtn+/Fy5cSMuWLYmMjGT48OHce++95fp+Li4m5oyyDTi/2Ki8+PFKjUojGpvHjx9n06ZNxMXFERcXx5133snjjz/O6dOn6dOnD08++SSRkZE0aNAAwJBGrohIbePiAq6u8Ke3fBWmRfJX17Ch8c1Nkwm8GxibWRG6llC9eXpBRKTtIVLVVXjlpslkegR4F8jCNv3sMLbrYiOx3fS/HBhtLec30spNERGRynW5Oy0v0h2XIiIiVZfVamX//v0kJCQQHx+Pt7c3r7zyCkuXLmXevHlEREQQGRlJZGRkqVc6lrZhWZ7GptVq5eDBg8TGxjJkyBACAwNp3bo1J0+eJCoqiqioKG6++WY6d+5czt8RERG5kgX/hkyD98hs0cK2B59c3k8/wYafjM1s0gQmP2psZnnpWoKIXEmVXLkJpAIxwOo/rtA0mUzPAVuBUdgancsN+F4iIiLiYJe70/Ii3XEpIiJSdZlMJtq2bUvbtm0ZN26c/fnQ0FBuueUW4uPjWbJkCadOnSI/P5/8/Hw++ugjIiIiCA0NpW7d/50xVpoVnKVvgFpwcXEhLy+Phx9+mLi4ODIzM2ndujUtWrQgMDCQzZs307RpU1xcXBzyeyQiIjaBgcY3NzUh/Oo6tDe+udm+vbF5FaFrCSJSmSr8bsFqtf5otVpX/Xn0rNVqzQbmX/h0YEW/j4iIiDheWloaixcvvuoxixcvJi0trZIqEhERkYrq0KEDTz31FCtWrCArK4u0tDRcXV3Jzs7ms88+Y8CAATRo0ICIiAj7v/FHjhzh4gCmiw3O0WFB9sxlyRk8vXwH50ssV2xsFhWdY8OGDcyePZvhw4fTqFEjsrOzadCgAUFBQbzxxhtkZGSwf/9+Bg4cCNjGzKqxKSLieD16VI/MmiQg0LZvoZHCwo3NKy9dSxCRyubodwzFFz6ed/D3EREREQNc7U7Liy7ecSkiIiLVj8lkomlT2w7LXbp0YevWrZw8eZIff/yR0aNH07RpU86dO0dwcDBBQUGMGjWK1157jQMH9l+2wdnu+e/sjc2SwpOEWtMINP8XFxcTiYmJDB8+nB9++IHw8HA+//xzfHx8cHFxYe7cuYwZM6bU43FFRMRYAYHGrrRs1QqaNjMur6YaMsS4rNAw8PU1Lq8idC1BRCpbhffcvGKwyVQH2AZ0A4ZbrdY11zj+SptqdgoNDfXSnpsiIiKOdbX9Mf5M+2WIiIjUXFarlYyMDOLj44mPjychIYFnnnmGW265hSeffJKffs0m3S0I18YtqOsXTOG+reTFfkJxzmEaNWrEwIED+eKLL7BYLJSUlFx23K2IiDhfdhYsWAAWy7WPvRpXV3j4YWjib0xdNd03q6Cil7obNoRJk6CuhzE1VYSuJYjItVTVPTev5B/YGpvfXquxKSIiIs5XmjstL9J+GSIiIjWXyWQiODiY4OBgxowZc8nXOnfuTGpqKttWvwEurnC+CBeP+rjUb8TP23fg28iHTz75hCVLlhAYGEhQUBCtWrXC3d3dST+NiIhcSbPmtpWEa9dWLOf6G9TYLIvhN0JeHpR3QquXF9w1rmo0NkHXEkTEORyyctNkMj0OvAXsAfpbrdYTFchKDg0NDdXKTREREccpy52WF+mOSxERkdrl7NmzvPHGG7z40kzOF5+jXvcb8O5xAyWncrCeL+a+8XcyvoOJJ598ArPZTEZGBqdPn2bbtm307NmTYcOG4eLiQlBQEEFBQQwbNoyoqCiOHj2Ki4sLfn5+mEwmZ/+YIiK1itUKG36CDRvKd/6QIRAVbWhJtcL58/Dtt7AtpWznNW0Kt98OjZs4pq6y0rUEESkNR6zcNHzPTZPJNAVbY3M3MKgijU0RERGpHGW50/Ii7ZchIiJSO1itVqxWK3l5+bz2zgIsrm7U7349fjc8St3m7fFqH0G9ztEsS87gk1Qra9euY8+ePRQUFJCXl0e3bt0AuPvuu4mKisLNzY3k5GRSU1MBePHFF2nSpAmenp60bduWsWPHApCens5bb73F8uXLSUhIID09vcyvV0RE5OpMJhg4CO4YC/Xrl/48b2+46y41NsurTh2IiYFx42wNy2vx9LT9d3rooarT2ARdSxAR5zF05abJZJoGvAH8AgyxWq1HDcjUyk0REREHKs+dlhfpjksREZGa7ZdffmHatGk8+OBDJLt24vPEQ5zesZb6IUMZ06cVr4wM4dkvd7IsOcN+zuiwIOaM6o6LS+lWYZ49e5bMzEwyMjIwm81YLBbGjRtHUlISjz/+OBkZGWRlZXH+/Hl27dpFly5dGD58OJ6engQFBREYGMjQoUMJDw/nxIkTeHh44OXl5ajfEhGRGquwEFKSISnJNjb1cnx9ITwceoWCRxUZi1rdWa2QkQ6/pUJWpu333mq1NTSbN4eWLaFTZ3Bzc3all9K1BBEprSq956bJZHoa2z6bPwPDrFbrcaOyRURExHHKc6flRdovQ0REpGY6ceIEL774IvPnz2fUqNv5Mceb5V+9R/3uw/DuOfySBuacUd0B7A3Oix9L2+D08PCgTZs2tGnT5pLnw8PD2bx5M2B7zXH06FEaN24MQExMDOnp6ZjNZnbt2kXTpk0JDw9n+vTpLFq0CB8fH4KCgoiIiGDBggUcPnyYNWvW2PcBDQwMxNfXV2NwRUT+wNMT+kdBv/6Qm2trtBWcAhO2lZrNA8DHx7baU4xjMkFwC9ujOtG1BBFxJkNWbppMpheAmUAycL2Ro2i1clNERMRxKnKn5UW641JERKTmefjhh0lMTOSNN97km6MNWfDmHApSvqHZvW9w15Dw/2lcWixWnl6+o0IrOI1w8uRJ0tPT7atAXV1duffee4mLi2PKlClkZGSQk5MDwN69e2nXrh1/+ctf7M3QwMBABg0aREhICAUFBXh6elKnjmH3hYuIiNQIupYgImVRJVdumkyme7E1NkuAWODxy9z5eNBqtS6q6PcSERERY1XkTsuLdMeliIhIzbBu3TpWrlzJvHnzeO211/Dw8OS5lbtYuPhj8hOW0fSOWZdtbAKGrOA0QoMGDejatStdu3a95PmoqCh+/vln4PcxuC1atMBqtTJw4EAyMjJIS0tj48aNNGzYkJCQEB555BGWLl1Ks2bNCAoKon///rz++uscPnyY2NjYS1aBenp6VsrPJyIiUhXoWoKIOFuFV26aTKaXgBnXOGyD1WodWM58rdwUERFxACPutLxId1yKiIhUX2lpaUyfPp1vv/2WqVOn8vLLL+PqWoenl+/g0x8SyFz4GH7XT+b++++/ZqOyqqzgNMKxY8c4ePCgfRWop6cnEyZMYN26dUyePBmz2cyZM2cASE9PJzAwkFtvvRV/f39743PAgAF06NCBs2fPUrduXY3BFRGRak/XEkSkrKrkyk2r1foS8FKFKxEREZFKZcSdlhfpjksREZHq6eDBg3Tp0oXrr7+eX375hQ4dOlzSoKzjG4j/7TO4Z9TNpWpQVpUVnEZo0qQJTZo0oXfv3pc8P3ToUFJTU7FareTl5WE2m2nevDklJSWEhoZiNpvZunUrK1aswN3dnQ4dOnD33XezevVqAgMDCQwMJDo6mlmzZnHo0CFSUlLszdCmTZvi6urqpJ9YRETk2nQtQUSqAkP23HQkrdwUERExnpF3Wl6kOy5FRESqB4vFwscff0z//v1p164dKSkphIaG2r/+w65sHnw/lry4JfhEj+eOyPZlbkxebgXnv+8O4/quzQz9WaqL9PR09u/fj9lsJiMjAx8fHyZOnMjXX3/N5MmTycrKwmKx4OrqSlZWFn5+ftxxxx00b97cPvq2f//+tGrVipKSEjVARUTEKXQtQUTKo0qu3BQREZHq57vvvjP0zQjY7rj87rvvmDJliqG5Ur0dAhYBm4CfgTzADWgHhAOjgBsAXaIVEakc8fHxTJ06ldTUVD7++GPatWt3SWMTYHDHxtTb9A5H0s3c1qt8I2X/vIJz6pD2tbaxCRAcHExwcPD/PB8TE0NMTAznz5/nyJEjmM1m/Pz8KCoqok2bNpjNZnbs2IHZbOall16iVatWjBw5kri4OHvT87rrruPpp5/m8OHD7N692/68j4+PxuCKiIihdC1BRKoKNTdFRERqofHjx1NYWMjp06cNy6xXrx7jx483LE+qt2xgKvAFYPnT14qBHRceHwKtgbnAbZVZoIhILfTCCy/wyiuv8OCDD7J69WqaNGly2eOmT59OfsZePlzyDXcO6lXuUbIXG5zDujSt1Y3N0qhTp459ZC2Ah4cHc+bMueyxr732Gvv27bOvAm3YsCFga1xPmjSJ3NxcALy8vMjKysLT05MHHnjAnh8UFETfvn0JCAjAarWqASoiIqWmawkiUlVoLK2IiIiIGGo1cA9woozn3Q38G/AwvCIRkdqrsLCQxMREBgwYwObNm6lXrx49evS44vEbNmzgxhtvZOPGjYSHh1dipWKUM2fOkJmZSUZGBtdddx2nT5/m2WefxWw22xuic+fOZezYsYwYMYKff/7Z3vQcOHAgU6ZMIT09nQMHDtgboh4e+tdZRERERMpHY2lFREREpEr7EhgDlGdQ0cfAUeAroK6RRYmI1EJWq5Xly5fz17/+FS8vL3bs2EG/fv2ued6AAQPYuXOn9r2qxry8vGjXrh3t2rUDoH79+sybN++yx7788svs3buXjIwMzGYzLi4uAKxfv55JkyZx9uxZAPz8/MjIyMBqtTJ16lT76NugoCBCQ0OvuApYRERERMQR1NwUERGRMivB1oQqBnyABs4tR6qI34BxlK+xedEa4BngDUMqEhGpncxmM+PGjSMxMZHnnnuOJ598kjp1rv72f/fu3bzwwgt8/PHHamzWIiEhIYSEhPzP8/fddx/33nsvJ06cwGw2k5WVhYeHB3l5eVgsFjZv3mxfBbpgwQJuv/12br75Zvbu3Wtveg4aNIj777+fjIwMsrKyCAoKwt/fH1dX7bQtIiIiIhWj5qaIiIiUSi5NxUtPAAAgAElEQVTwEbaVeduAU3/4WmugP/AgMADQzk21jwW4HzhrQNZbwO3Y/kyJiEjpHTt2DG9vb/z8/OjVqxdLliyx7+F4rfNuvvlmoqOj8fT0rIRKpTowmUz4+fnh5+dH9+7dAfDx8eH999+/5LiL2x298MIL7N271970PHPmDABfffUVjz32GFar1b63aFpaGmfOnOGFF16wrwINDAyke/fu+Pj4VO4PKiIiIiLVjvbcFBERkas6D8wFZgJnSnF8OPAB0N2RRUmV8z1wo4F5N1zIFBGRaysqKuKf//wnf/vb35g7dy4TJkwo9bnnzp1j6NChAKxbt466dTUYXIxXXFxMdnY2ZrOZo0ePEhMTw9GjR5k2bZp9JK7ZbGbZsmWMGDGCmJgY0tPT7U3PwYMHc8cdd5CZmUlubi5BQUE0aNAAk0m31ImIiIhUddpzU0RERCrVMeAWIL4M5yRha3C+BUxyRFFSJb1rcN4aIA3QYMTL+wXYCPwMHMf2or41EAYMBXydV5qIVLI1a9YwdepU8vPzefvttxk/fnyZzv/666/JzMxky5YtamyKw7i5uREcHExwcLD9OX9/fz799FP751arFYvFAsCTTz5JamqqfRXo0aNHAfjkk094+umnAahXrx6tW7dmx44d5Ofn8//+3/+zj8QNDAykU6dO1K9fvxJ/ShERERGpLFq5KSIiIpd1ArgOWxOlvN4GHjOmHKnCSrDtu1qalb1lMR942ODM6m4lMAdIuMoxHsBY4EVsDU8RqZmKi4txc3Nj9uzZnDp1iueeew5vb+8yZVgsFlxcXDh58iQNGmgHbakeTp8+bW96njhxgttvvx2z2cyUKVPsq0Czs7P57rvvuOGGG4iJieH48eP2puegQYOIiYkhOzubwsJCAgIC1Nh3EIsFDh8GsxmOH4Pz58HNDfz9ITAIggLB5OLsKkVERMTRtHJTREREKs3DVKyxCTAN6Av0qXg5UoX9hvGNTQDd2va7E9j+Tn5RimPPAouAZcBrF87T0D6RmiM/P59Zs2axbt06kpOTef7558uVs3z5cubNm8f69evV2JRqpV69enTo0IEOHTrYnwsMDGTFihX2z4uLi+2/fuSRR9i7d6+98Xnw4EEA5s+fz9/+9jcAmjRpQocOHYiLiyMnJ4d33333klWgbdq0wcPDo3J+wBrgfDEkJEBSEuTnX/k4X1/o0wfCe4Ora+XVJyIiItWfmpsiIiLyP76kdE2Ua7EA9wHbATcD8qRqyqxmudXNEWAIsKuM553GNhp6P7bVnmpwilRvJSUlfPjhhzz//PP4+/vz5ptv4lrObkBSUhJ33303c+fOLXeGSFXm5vb7K8+bbrrpssfMmDGDRx991L7fZ/6FLlx+fj6xsbH2Zmh+fj4//vgjgwYN4tZbb+XUqVOXrAIdOnQox44do6SkBH9/f1xcavdSRLMZVq6A48evfeyJE/D997B9O9x2GzTxd3x9IiIiUjOouSkiIiL/4xUDs34FvgZGGZgptUPV3jyhchQBf6Hsjc0/ehUIBKYaUpGIOMuhQ4d48cUXmTFjBg8//DB16pTv7XxGRgYxMTE89NBDTJqk3bGl9jKZTDRp0oQmTZrQs2dP+/Nt2rRhzZo19s9PnTqFu7s7AOPGjWPfvn1kZGSwa9cumjVrxtChQ5k7dy5z5szBzc2N5s2b06VLF7777juOHTvG4sWL7c3QoKAggoKCyv33t6rbtxc+/9w2frYssrLggw9g3Hj4w7asIiIiIldUM19NiYiISLmlAEkGZ85Hzc2arHk1y61OXsGY8bzPAMOBjgZkiUjlOXToEE899RSPPvooAwYM4NChQ/YmS3mtXbuWXr16MXfuXIOqFKnZ6tevb//16NGjL3vMrFmzmDx5sn215+nTpwHIyclh5cqV9tWhRUVFbNq0iX79+jFq1CiKi4vtTc/rrruOqKgocnNzcXV1rXbjorOzytfYvOjcOfh0CUx8GBo1MrY2ERERqXlq96wMERER+R8/OSBzE1DO6xxSDXQEPB2Qa9gu89VUNjDboKyzwNMGZYmI4505c4YZM2bQqVMncnJyaNKkCUCFGpsWi4XTp09z//338/XXX9fYlWMizuDm5kaLFi3o168fo0eP5r777gOgU6dOxMbGsn//fgoLCzly5AhhYbZXOCNGjKBHjx6cPXuWDRs2sG3bNsDWKG3YsCENGjSgc+fOjBkzBoAjR47w7rvvsmrVKlJSUjhy5AgWi8UpP++flZyHlSvL39i86OxZ+PorsFaNH0tERESqML2bERERkUukOCCzENgDdHNAtjhfHWAwsNrg3CEG51U37wPFBuatAg4DLQzMFBHHmDhxIvHx8SxdupSYmBhMporvmvvcc8+xbds21qxZo302RZzAxcUFf//fN5W82AD9s1mzZjFx4kT7KtDiYturgezsbD744AMyMjI4cuQIAImJiYSHhzN69GhcXFzsY2+jo6MJDw+noKCAunXrVnjF97Vs2wYXSqqwgwfh1z3QpYsxeSIiIlIzqbkpIiIilzjmoNyjDsqVquERjG1uDgE6GJhXHX1hcJ4FWIH23hSpqpKTk1m3bh1PP/00r776Kr6+vtStW9eQ7IULF/Lmm2/y448/GpInIo5Tr149OnXqRKdOnS55vkePHiQl2TaPKCoqIisri2bNmgFw3XXXceDAAcxmM1u2bMHNzY3w8HCeeeYZ/vWvf+Hv709QUBC9evXi/fffJzs7mzVr1thH4gYGBuLt7V2ueq1WSEys2M/8Z0mJam6KiIjI1am5KSIiIpdw1Mx6rRGp2W4EwjFuv9b/z6Cc6qoQ+MUBuUbs3ykixjpy5AjPP/88ixYt4p577qGkpITmzY3bdXjDhg08/PDDLFy4kH79+hmWKyLO4+7uTsuWLe2fT5ky5bLHzZo1iwkTJmA2m8nIyLA/f+jQIebMmUNGRgYFBQUA7Ny5k27dujF27Fg8PT3tTc+oqCi6detGYWEhdevWxcXl0ncLx4/DUYPvYjxwAM6cBq96xuaKiIhIzaHmpoiIiFzCUSMrNQqzZnMFFgGhQFEFsyYDAyuYUd0dBEockJvqgEwRKb/U1FTCw8Pp1q0b8fHx9O7d2/DvsXfvXp577jnGjRtneLaIVG2+vr74+voSGhp6yfN9+/Zl9+7dABQUFGA2m2ndujVgWyF6+PBhtm/fzurVq7FYLHTr1o3HH3+cxYsXExAQQFBQEOHh4bzxxhts357Frl1xeDcIpEGDILzrN8fV1a3CtWdmQbt2FY4RERGRGkrNTREREblEmAMyGwGtHJArVUtXbA3OcYC1nBmDgLlGFVSNGbnX5h9VtPEsIhVntVpZvXo1ffv2pX379ixdupQbb7zRkH01/yg3NxeABx980NBcEalZvL29LxmB++yzz172uJkzZ3LvvffaV4FeHJu9c2cqP6z9PwoKMrFYigETj035DT+/9iz/cjwedRvaG5/BQZH4+bUvVV05Of8/e3ceHmV5t338Owkh7LuyqeyRfUeRiohaUWQHKaiolapFrUprtfra4lJrXVrB1pZH7eNSXKA+QkFFQUErmwgSFlmCCAoKCIgQdpLM+8egdQHNck/umeT7OY45LMl9n3OKpGHym+u6HG5KkqRjc7gpSZK+4TxiW9PmBZh5ARDsj2yVqIYDZYErgN0FvHcI8BRQLuhSSahKnHKrxSlXUv6sXLmS0aNH89ZbbzFp0iT69etH7969A3+ew4cPc+GFF1K7dm2eeeaZwPMllT5169Y96pbZrVv1YPSNG8iL5rFv7zZ2Z39C1WoNiEajVKvWkN27N7F+/Syysz/h1FOuz/dwMzceW1hIkqQSw+GmJEk/YCvwLrHz7/YB5YGWQBegXoi94uUkoA8wNcDMUQFmKfENBk4BriN/f47qEVut+RMcgn+pAVAV2BVwbruA8yTl3913381dd93FwIEDWb16NQ0bNozL80SjUa677jqysrKYMGFCXJ5Dkr6UfuRdaSmRFCpVqk2lSrW/+tzZZ/2+8LnpRW0mSZJKMoebkiQdRRR4BXgYmPE91/UEfgEMoGQNZe4k9u+fE0BWX+C0AHKUXE4E/k3sjMf/BeYBmUA2sZXBTYltgTwY6AcU/WSmkiUCdAOmB5zr16JUvHJycsjKyqJly5a0b9+e119/nR49esT1OceNG8czzzzD3LlzqVOnTlyfS5Lq1P7haxIpV5IklQwONyVJ+patwM+BKfm4dvaRx/nAo8AJcexVnNoDtwN3FDGnOjCekjX4VcFkAH/82q9ziQ03/TPxw64g2OFmLWKDZEnFY9asWdx4443k5OSwYsUK+vbtWyzPW716dZ577jnatXOttqT4q18fIhGIFvbA9aMoUwZqO9yUJEnfIyXsApIkJZIsYtvN5mew+XXTgc7A8sAbhed24OIi3F8RmEbJ3LpXhZeKg8386g80DjDvGjzPVCoOmzdvZvDgwfTq1YtzzjmHefPmkZIS/5feq1atYuvWrVx22WXFNkiVpIqVICMj2Mw2baGM23pIkqTv4XBTkqQjtgHnABsLef9W4MfApsAahSsVeAq4mYIPoxoTW9H6o6BLSaVIGvB4QFktgFsDypJ0dHv27CEvL4/09HTS0tJYvnw5f/7zn6lWrVrcn3vLli2cd955jBs3Lu7PJUnfdmrX4LIiETj1lODyJElSyeRwU5IkYmdsjqLwg80vbQWuPJJXEqQC9wFzyN9ZfZWBm4BlxFbASiqansRWURdFZeBZXLUpxUteXh7//Oc/ycjIYNKkSdSoUYPnn3+e5s2bF8vz79+/nwEDBtC0aVPuvPPOYnlOSfq6Ro2gfftgsk7rBrU9LliSJP0Az9yUJAmYCfxfQFmvApOBQQHlJYJuwDxgCbF/t8XAB8BhoBrQgdgqzQuJDVIkBecuIIdvnl2aX9WBl4mdoyspeO+88w433HADq1atYsyYMQwaVPzf/UeOHMnOnTuZPn06aWnu4ygpHL3Og08+gW3bCp9xwgnQ88zAKkmSpBLM4aYkScBf45BXkoabX+pw5CGp+ESAe4HTgauAT/N53wXA/wD149RLKs2i0SiRSIQnnniCtm3bMnXqVI4//vhQugwZMoQ777yT6tWrh/L8kgRQrhxceilMmABbtxb8/hNPhIsu8qxNSZKUP5FoNLE3zotEIos7duzYcfHixWFXkSSVUDuBWkBewLmbcKggKVh7iG0x+yjwHt/dArsisaHmNcAZFPy8XEnf78CBAzz00EPMmTOHl156CYBIJJyvtJdffpm2bdty4oknhvL8knQ0hw/BrNmwYH7+rk9Jge5nQPfukJoa325KXnl5sGE9fLwRtm6BAwdif16q14B69eDEEyB7Dxw8CKkpUKMm1KgOEQ9kk6SE0KlTJ9577733otFop6AyXbkpSSr1FhP8YBNgEQ43JQWrErHVm1cRG3QuBT4HUoDGQAaxs3IlBSsajTJlyhR+9atfkZOTw4MPPgiEN9icP38+gwcP5tFHH+XSSy8NpYMkHU1aWejVCzp2hEXvwvLlsH//d6+rWBHatYPOnWMDKulo8vLg3YWwYAF88cVRLlh37HvT06FlS+jSBerWi1tFSVJIHG5Kkkq99+OUuwLoH6dsSapE7KxbSfG3YsUKLrnkEm655RZuuukmKlSoEFqXDRs2MGDAAH7xi1842JSUsI47Ds7vDeedDzt3xs7izMmBtDSofTxUqQohvT9ESeLzHfDii7GzXAvj4EFYsiT2aN8+NnQvVz7YjpKk8DjclCSVekd5I3FC50qSpPjbsWMHY8aMYdSoUbRp04ZNmzaFfq5lbm4uAwcO5LTTTuOPf/xjqF0kKT8iEahRI/aQ8uuzz+Dpp2Dv3mDyMjNh/Xq4ZATUqhVMpiQpXO48Lkkq9eK19sI3hUqSlHwOHz7MX/7yF5o1a8b8+fM5fPgwQOiDTYDU1FTGjh3LhAkTSPVwOklSCbR/H0z4Z3CDzS/t2hUbmO462va2kqSk43BTklTqtYpTbps45UqSpPgZMWIEv//973nwwQd59913ad++fdiVALj//vtZu3YtPXr0oFKlSmHXkSQpLl59FbKz45OdnQ3//jdE8+KTr3BEo5CXG/unpNLDbWklSaVeJ2Lv9gn69U3ngPMkSVJ8fPDBB8yfP58RI0Zw55138uijj1KlSpWwa31l/Pjx3HHHHfTs2TPsKpIkxc2WzbBsWXyfY/16yFwKHTrE93kUX1u3wJJM2LQRtm6Nnen75TbY9epBy1aQkQEpLu2SSiy/vCVJpV41oG/AmWcD9QLOlCRJwdq9eze33HILLVu2ZOrUqUSjUU4++eSEGmy+/vrrXH/99Tz99NN06dIl7DqSJMXNu+8Wz/MsmO8qv2S1Y0dse+Hx4+GdBfDJJ7HBJsT+m+7YAcuXw8Tn4eFxsHpVuH0lxY8rNyVJAq4H/h1g3i8CzJIkScF7//33Ofvss6lRowYvvfQS5557btiVvmPfvn1cfPHFjBkzhiFDhoRdR5KkuIlGYfXq4nmuzz6DTz+F+vWL5/kUjCVL4JWX/zvM/CG7dsHEidCuHfTtC6lOQqQSxS9pSZKAs4BhwPMBZPUF+gWQI0mSgjdv3jzatWtHRkYGf/jDHxgxYgRpaWlh1zqqChUq8Oabb9K8efOwq0iSFFe7dsG+fcX3fJs2OtxMJu++GxtsFsbSpbB/Pwz9CaSmBttLUnjcllaSpCP+CjQqYkY9YDwQKXodSZIUoI0bN3LRRRdxxhlnMHv2bNLS0rjiiisScrB58OBBLrnkElatWkWLFi2IRPybhSSpZNv5efE+35Ytx/5cNA/27oU92ZBzuPg66eg2biz8YPNLWVnw5puB1JGUIFy5KUnSETWB14FzgPWFuL8+MBPP2pQkKdE8+OCD/O53v6Nr164sWbKENm3ahF3pmKLRKFdffTVz586lZs2aYdeRJKlY5OYV7/MdPPjNX+/bB5lLYkOwzZvh0KHYxyMRqFULGjSATp2gTt3i7Vna5eTAv6cEkzV3DrRoAfX8oY1UIjjclCTpaxoDC4mdmVmQLWoHAH8H6sSjlCRJKrBoNMqWLVuoW7cuVatW5ZlnnmHAgAEJvwry/vvvZ/LkycybN4/jjz8+7DqSJBWL8uWK9/m+3J40NwfenhMbfB3tLMdoFLZtiz0WLYImTaBPH6hWvXj7llbvvw87dgSTFY3G/jtfODSYPEnhcltaSZK+pRbwHLFVnP059jfLCHA+8DLwIg42JUlKFEuWLKFHjx6cd955RKNRrrzySgYOHJjwg82tW7dy7733MmnSJFq1ahV2HUmSis3xx8dWSRaXGjVh9254/HF4682jDzaPZt06+NvfYOXKuNbTEYveDTZv1SrIzg42U1I4HG5KknQMZwNTgG3Etpt9CPg98CfgVeAz4BWgN56xKUlSIti+fTtXXXUVXbp0oVGjRkyfPj3hB5pfikaj1K5dmw8//JBevXqFXUeSpGKVVhbqFuOWr9WrwZNPfP/Zm8dy+DC88K/YqkLFz6GDsGlTsJnRKHy0IdhMSeFwW1pJkn5ADWLncJ4TdhFJknRUOTk5lClThr1797J27Vrmzp3LqaeeGnatfPvkk0/o168fEydOpGnTpmHXkSQpFB07waefxv95ypWDzEzYubPwGdEoTJkMdevEVoEqeIUZPOfHp5uhdeIevy4pn1y5KUmSJElKWq+88gqtWrVixowZNGjQgNmzZyfVYHPv3r3069eP4447joYNG4ZdR5Kk0LRpA5Uqxf956tWDjz4qek5ODkydGht0KnjZe+KTu8dtaaUSweGmJEmSJCnprF69mt69ezNw4ECGDBlCt27dwq5UYHl5eVx66aUcOHCAiRMnUqaMmytJkkqvsmWhT9/4PkfFirB9e3B5H30EGzcGl6f/itfBAklyYoGkH+ArJ0mSJElS0rntttsoX748q1atonHjxmHXKZS1a9eydOlSZsyYQdWqVcOuI0lS6E4+GbqeBgvmxye/c2d4661gMxcvgpNOCjZTULlyfHIrxSlXUvFyuClJkiRJSni5ubn84x//IDMzk7/97W8899xzpKenh12r0Pbv38/JJ5/M6tWrXbEpSdLXnPvj2Kq9+QEPOHtfALt3BZsJsGFD8JmCOnViqyyD3va3Xt1g8ySFw21pJUmSJEkJ7a233qJTp07cdttttGnThmg0mtSDzbfffpvGjRvz2WefOdiUJOlbIilwbi8YflEwq/cqVoSfDIMuXWDz5qLnfdvu3bA3TudDlmZpZYNfEZuSAh5xLpUMDjclSZIkSQlr4cKFnHPOOfTo0YOsrCxGjRpFJIkPS/rggw8YOHAgI0eO5Pjjjw+7jiRJCSsjA35xPfTvDyeeCKmpBbu/XDno2hWuuQaaN499bO/e4HvGM7e069w52LyWLaFipWAzJYXDt4hKkiRJkhLK3r17eeCBB7jyyivp0qULWVlZNGrUKOxaRbZz50769OlDz549ueuuu8KuI0lSwktLg/YdYo/cHNi+HQ4cgJRUqF4ddu2CTRthyxY4eDA2AK1RM7b1aOPGsdV/Xxev90cl8fuuElqLlnD82/DZZ0XPSkmB07sXPUdSYnC4KUmSJElKCNFolGeffZZbbrmF8uXL06dPH+rXr18iBpsAGzZsoEmTJjz11FOkpLiRkiRJBZFaBmrX+ebHKlWC+vXzn1G1any2pq1SJfhMxYbV/QfA448V/ezNM3pA7drB9JIUPl9NSZIkSZISwvDhwxk1ahQ33HADK1asoHPQe5GFJBqNsmnTJjp06MDLL79MhQoVwq4kSVKpVLdu8Jk1a0J6ueBzFVOvHvTrX7SMVq2gu6s2pRLF4aYkSZIkKTSbN29mxowZANx4441kZWXx61//mvT09JCbBefhhx+mS5cu7N+/P+wqkiSVak2bxSGzafCZ+qb27WHIEChb9oev/bYuXWDQoNi2tJJKDr+kJUmSJEnF7uDBg9x3331kZGQwbtw4otEoXbt2pU6dOj98cxJ55ZVXuOmmmxg/fjzly5cPu44kSaVavXoF28Y2Pzp3CTZPR9eqNVxzDZx8cv6ur1ULRoyA3hfEzmiVVLJ45qYkSZIkqVitWLGCAQMGcPDgQR599FGGDRtGJBIJu1bgli9fzrBhw7j33nvp37+I+6lJkqRA9DwLJvwzmKx27WJDNBWPqtVg2HD4/HNYmgmbNsGWLXDwYOx8zlq1oG49aNUSGjaCEvjXS0lHONyUJEmSJBWL1atX07RpUxo0aMAVV1zBDTfcQMWKFcOuFTc5OTlce+21/OpXvwq7iiRJOqJJE+jYCd5bXLScSpWg13nBdFLB1KgRG1JLKr3cllaSJEmSFFeff/45119/PW3atOGNN96gcuXK3HbbbSV2sHngwAEyMzPp0KED9957b4lclSpJKt2ieRCNht2i8M4/Dxo3Lvz95crBRReDO85LUjhcuSlJkiRJiptHH32UW2+9lQYNGjBr1iy6d+8edqW4ikajjBw5kuXLl5OZmUlKiu8pliQlv+3bYEkmbNoY2wb00KHYlp81a8bOsWzREjKaJc/ZhmXSYPhwePllyMws2L21asGQC6F27fh0kyT9MIebkiRJkqTA7dmzh0qVKrF582b++Mc/csUVV5CamiQ/8SyCu+++m+nTp7NgwQIHm5KkpPfFF/DKy7B27Xc/F43C9u2xx7JlUKVKbJvWli2Lv2dhlEmD/gNig9nXZ8K2bd9/fXo6nHIKnHFG7F5JUngcbkqSJEmSAvPhhx9y0003sXXrVubOncuYMWPCrlRsJk2axO9//3teffVVMjIywq4jSVKRrFgB06bGVmnmx+7d8K9J0KYN9OuXPAPAjAxo1gw++giy1sCnn8aGutFobNvZunXhpJOgVWsoWzbstpIkcLgpSZIkSQpAdnY29957L3/6058455xz+N///d+wKxW7Nm3a8PTTT3PWWWeFXUWSpCJZuhSmTC7cvcuXw759MGw4lEmSnz5HItCwYewhSUp8SfLtRZIkSZKUiKLRKJFIhHXr1jFlyhQmT55M7969w65VrD7++GPWrVtHz549adGiRdh1JEkqki2bYeq/i5axbh288Qb06hVMJ0mSvs4DQCRJkiRJhbJgwQK6devGkiVLaN++PStWrCh1g83s7Gz69u3LX/7yl7CrSJJUZHm5MGUK5OUVPWvBfNi4seg5kiR9m8NNSZIkSVKBfPLJJ4wYMYLTTz+dtm3bcsIJJwCQklK6XmLm5uZy0UUXAfDUU0+F3EaSpKJbswa2bg0u7+3/BJclSdKX3JZWkiRJklQgI0aMIC8vj0WLFtG+ffuw64Tmzjvv5N1332XhwoVUrlw57DqSJBXZokXB5q1dC1/shGrVg82VJJVuDjclSZIkSd8rGo3y4osvsmbNGm677TZeeOEFqlevTiQSCbtaqC6//HL69+/PSSedFHYVSZKKLCcHNmwIPnf9eujgcFOSFKDStWeQJEmSJKlAli5dyllnncWll1761TCzRo0apXqwOWvWLKZNm0bjxo3p1KlT2HUkSQrEts+COWvz2z7dHHymJKl0c7gpSZIkSTqqt99+m06dOlG/fn3WrFnDrbfeGnal0K1Zs4bBgweTmZkZdhVJkgKVnR2f3D1xypUklV4ONyVJkiRJXzl8+DCPPPIIu3fvplu3bixYsIAJEyZwwgknhF0tdDt27KBPnz707t2b22+/Pew6kiQFK06bMpTizR4kSXHicFOSJEmSBMBrr71G27Ztufvuu1m9ejWpqal07tw57FoJ4xe/+AXHHXcc//jHP0r1trySpJKpcuX45FaKU64kqfRyuClJkiRJ4tJLL6Vfv37079+frKwsTjnllLArJZwHH3yQKVOmUK5cubCrSJIUuOOPg9TU4HPr1Q0+U5JUupUJu4AkSZIkKRy7du1i3bp1dOzYkaFDh/K73/2Opg2hfGYAACAASURBVE2bhl0r4Tz00EPUr1+foUOHhl1FkqS4SS0DDRvCunXB5jZqFGyelGi+2AkffQxbNsO+fbGtmKtVg7r1Yl9T6elhN5RKHoebkiRJklTK5Obm8uSTT3LbbbfRoUMHXn31Vfr06RN2rYQ0ZcoUbr75ZqZOnRp2FUmS4q5z52CHmxkZULVacHlSIln/Icyd+/1fM2XLQtt20P10qFK1+LpJJZ3DTUmSJEkqRVauXMmIESNYv349d911Fz//+c/DrpSwlixZwsUXX8yf//xnzj///LDrSJIUdxknQ926sHlz0bMiETjjjKLnSInm0EF49TVY8l4+rj0Ei96F5cug13nQoUP8+0mlgWduSpIkSVIpsGXLFqLRKNWrV6d79+6sXbuW6667jjJlfM/rsYwePZrLL7+c6667LuwqkiQVi5QU6D8g9s+iOq0b1D+h6DlSIjmwH556Kn+Dza87eBCm/hveeB2i0fh0k0oTh5uSJEmSVILt27ePO++8k8aNG/PWW29Rt25dxo4dS82aNcOulrCiR37i9OKLLzJu3DgikUjIjSRJKj61a8OAgbGVl4WVkQFnnRVcJykR5OXBxInw6aeFz5gzBxYuDK6TVFo53JQkSZKkEmrixIk0b96cp556imeffZYePXqEXSnh5eXlcdFFFzFp0iRq1KjhylZJUqnUpg1cOBTS0wt+b/v2MHQopKYG30sK0zsLYMOGoue8PhO2by96jlSaOdyUJEmSpBImNzcXgJkzZ3LNNdewcuVKBgwY4ArEfPjtb3/LzJkz6dy5c9hVJEkKVYsWcM210Lx5/q6vXh2GDY9ta5vqe4NUwuzfD7NnB5OVkwMzZwSTJZVWfpuRJEmSpBJi69at3H777Wzbto0pU6bw+OOPh10pqTz99NM8+OCDvPHGGzRu3DjsOpIkha5KFfjJMNj5OWRmwsaNsGVL7PzA1FSoUQPq1YOWLaFJE4i4lEYlVGYmHD4cXF5WFnyxE6pVDy5TKk0cbkqSJClfVgEvAIuAtcAhoCrQFugGDD3ya0nF79ChQzz88MPcddddtGrVinHjxoVdKenk5uYybtw4HnvsMU4//fSw60iSlFCq14CenqGpUmzl+8FnrloFp3ULPlcqDRxuSpIk6XtlAr8CZh3j8+8BTwKjgZ8BdwFViqWZpC/NnTuXhx56iL///e8MHz6clBSXTRTEwYMHSU9PZ968eaQX5nAxSZIklVh5ubEVy0H79NPgM6XSwle8kiRJOqoo8HugC8cebH7dXmAc0AaYE8dekmJWrVpF//79Wb9+PT179mTdunVcfPHFDjYLaNeuXXTu3JmpU6c62JQkSdJ37NoVOyczaNu3B58plRa+6pUkSdJ3RIHrgN8CBX0N9zHwY+D1oEtJAmDnzp3ceOONtG3blrJly5KWlgZAuXLlQm6WfHJychg6dCjp6emcc845YdeRJElSAsrNTa5cqTRwW1pJkiR9x8PA34pw/wFgILAUaBxII0lf6t27N/v27WPmzJmceeaZYddJajfeeCPvv/8+CxcupEKFCmHXkSRJUgKK1+YebhoiFZ7DTUmSJH3DWuDWAHL2ACOJbWkbCSBPKs1mz57NRx99xOWXX85zzz3HiSeeSGpqati1ktrevXtZsWIF06ZNo169emHXkSRJUoKqVBnKl4f9+4PNrV0n2DypNHFbWkmSJH3D3UBQr9neBGYElCWVRuvXr2fIkCGce+65rF27FoCGDRs62CyirVu3UrFiRWbPnk2HDh3CriNJkqQEFonACScEnxuPTKm0cLgpSZKkr2wHJgWcWZTtbaXSbNasWbRo0YI9e/awbNky7rnnnrArlQgrVqwgIyODOXPmEIm4rlySJEk/rH3A74crWxZatAg2UypNHG5KkiTpK7OAgwFnzgByAs6USqq8vDxeeOEFDh06RNeuXZk8eTLTp0+nhT/5CMRnn31G3759GTx4MD/60Y/CriNJkqQk0fxkqFYtuLyOHT1zUyoKh5uSJEn6yqI4ZB4AVsYhVyppFi5cyI9+9CNGjhzJsmXLqFChAueff76rCwNy4MABBg4cyEknncT48eP9fZUkSVK+paRCv37BZFWtCmf2DCZLKq0cbkqSJOkrH8cp96M45UolQTQa5eqrr6Zbt260bt2arKwsOnfuHHatEmf//v00bdqUF198kbJly4ZdR5IkSUmmUWM4/fSiZZQpA4MGu2pTKiqHm5IkSfpKbpLlSsns4MGDrF+/nkgkQpcuXVi4cCGPPfYYtWvXDrtaibNkyRKqV6/OU089Rc2aNcOuI0mSpCR11tnQ9bTC3ZuWBsOGw0knBdtJKo0cbkqSJOkrxyVZrpSMotEoU6ZMoWXLllx77bUA/OxnP6Njx44hNyuZJk2axKmnnkpWVlbYVSRJkpTkIhHo1QuGDoWKFfN/30knwc9/Dk2axK+bVJqUCbuAJEmSEkc8RisRoF0ccqVktHbtWkaNGsXcuXO55ZZbuPnmm8OuVKItXLiQyy67jL/+9a9kZGSEXUeSJEklRIuWsW1ql2bC4sWwbdt3r0lJgcaNoUsXaNYMIi41kwLjcFOSJElf6RGHzM5ApTjkSslk7969VKxYkZycHI4//njWrFnDSe5HFVcbN26kX79+jBo1iquuuirsOpIkSSphypWDU7vGHvv2wuYtsG8fpESgWjWoXRvKpIXdUiqZHG5KkqQSZwvwOrAY2AhEgdrEViX2BNwF5tiaEfs9mh1g5tUBZknJJicnh/HjxzNmzBhee+01OnfuzLPPPht2rVKhatWqXHfdddx6661hV5EkSVIJV6GiW85KxcnhpiRJKjGWA3cDk4Gc77nux8BtwJnF0CkZ/YbghpsnAcMDypKSzcyZMxk9ejTbtm3j/vvvp0OHDmFXKhVyc3OZMmUKgwYN4vbbbw+7jiRJkiQpYO7yLEmSkl4e8HugE/Avvn+wCTCT2OrEUcC++FZLSucCPw0o6x9AhYCypGQRjUaJRqM88MADnH/++WRlZTFy5EhSU1PDrlYq3HLLLVx77bXs2LEj7CqSJEmSpDhw5aYkSUpqucBlwDOFuHc8sAKYjmdCfts4Yr837xYh4y7gnGDqSEkhOzube+65h+zsbB555BFeffVVUlJ8P2lxeuyxx3jkkUd48803qVWrVth1JEmSJElx4CttSZKU1G6hcIPNL80BhhE7l1P/VRmYQWyFa0GlAH8E3AxSpUVeXh5PPvkkGRkZTJ06lX79+gE42Cxm8+fP59prr+WJJ57g1FNPDbuOJEmSJClOfLUtSZKS1tvAnwPIeRl4IoCckqYa8DowlvyvbG0FzCM2dI7EqZeUaKZNm8bo0aO59dZbWbp0Kb169Qq7UqnUrl07nn32WYYNGxZ2FUmSJElSHDnclCRJSSkKjCa4FZc3A/sDyipJUoAbgE3AX4Az+O6g8wRgKPAasAxwvZRKg02bNnHVVVexY8cO+vbtywcffMD1119PWlpa2NVKnc8//5yHHnqIcuXKMWTIkLDrSJIkSZLizOGmJElKSguBxQHm7QAmBZhX0lQFrgPeAnYRG3Z+SOz3bSMwETgX/3Kpkm///v3cfffdnHzyyaxdu5bdu3eTkpJCzZo1w65WKh06dIjBgwczadIkDh8+HHYdSZIkSVIxKBN2AUmSpMJ4IQ6Z/wIui0NuSZMC1A+7hBSCaDRKjx492LZtG08//TSDBg0iEnED5rBEo1GuueYa1q9fzzvvvEN6enrYlSRJkiRJxcDhpiRJSkqL4pAZ5EpQSSVHZmYmmzdv5vzzz2f8+PG0aNGC8uXLh12r1Hv++eeZNGkS8+bNo3bt2mHXkSRJkiQVE3cOkyRJSSkrDplbgOw45EpKTtu2bePqq6+mc+fOzJw5E4COHTs62EwQgwcP5q233qJ169ZhV5EkSZIkFSOHm5IkKSnF62Q1T2yTBPDGG2/QrFkzMjMzmTNnDn/+85/DrqQjMjMzufnmmylTpgwdOnQIu44kSZIkqZg53JQkSUmpahwyU4CKcciVlDzmzJlDNBqlXbt2PPzww8yfP5+uXbuGXUtHbN68mb59+5Kdne15p5IkSZJUSjnclCRJSaldHDJbAOlxyJWU+LKysujTpw9nn302y5Yto1atWlx66aWkpPiSKVHs37+f/v3707x5cx5++GGHm5IkSZJUSvlKXZIkJaVuSZIpKbFFo1F+/etf07p1a8qWLcvKlStp1y4eb59QUf31r39l9+7d/Otf/yItLS3sOpIkSZKkkDjclCRJSekSIOgfbY8MOE9S4srNzWX79u1EIhGqVKnC9OnTefHFF2nSpEnY1XQMv/zlL3nzzTepVq1a2FUkSZIkSSFyuClJkpLS8cQGnEE5DTglwDxJies///kPnTt35qqrrgLgt7/9LWeffXbIrXQsEyZMYNSoUaSmplKnTp2w60iSJEmSQuZwU5IkJa0HgNoB5JQFHgc8vU1KHDnAFOByoA1QgdiZuHWA84B7gE8KmPnxxx/zk5/8hLPOOovu3bvz+OOPB9hY8TB37lxGjhzJqaeeGnYVSZIkSVKCKBN2AUmSpMKqCfwTuAA4XISccUDLQBpJKqooMBG4Gdh4lM9vBV478hgDXAz8Caj1PZm5ubmkpqby0UcfsXPnTpYuXUqrVq0Cbq6gffjhhwwYMIBf/vKXXH755WHXkSRJkiQlCFduSpKkpPZj4EWgfCHujRAbbP480EaSCmsvMBQYztEHm9+WCzwNtALeOMrno9Eozz33HBkZGWRlZdG9e3dmzJjhYDNJPPbYY3Tv3p177rkn7CqSJEmSpATiyk1JkpT0+gCZwE+Befm8JwN4AugWr1KSCmQf0Bv4TyHu/ezIvf8mtmUtwOLFi7nhhhtYtmwZv/3tb2nQoEFATRVvubm5RCIR7rnnHg4dOkRKiu/JlSRJkiT9l68SJUlSiZABvA28TGzYmX6Ua1KB04EJwDIcbEqJ5AYKN9j80iHgQuAjYis2r7jiiq9WbP76178mPf1o/6+gRDR69GhuuOEGUlJSKFeuXNh1JEmSJEkJxpWbkiSpxEghtnqrN7EzOFcS29oyCtQG2lC47WslxdcM4PGihhw8yJ6HH+bsnBzW3norCxYsoHx5v+KTzSOPPMLjjz/O22+/HXYVSZIkSVKCcrgpSZJKpDSg3ZGHpMR2R1FujkbhpZfgl7+E/ftZ96c/MQ/4kYPNpPPaa69x4403MnHiRDp16hR2HUmSJElSgnJbWkmSJEmhWQrML0rAxIkwdCgMHw5r1sBPfsLfA+qm4jV9+nTuvvtuBg0aFHYVSZIkSVICc+WmJEmSpNDMLMxNO3fCQw/BrbfCwIHQtSs0bPiNzCgQCaai4uyLL76gUqVKPPTQQ2FXkSRJkiQlAVduSpIkSQrNewW5OCcH/v53aNYMpk6FzZshPf0bg02Az4BNAXZU/Bw4cIALLriAMWPGEIlEiEQcSUuSJEmSvp8rNyVJkiSF5pP8XpiXB6efDuvWwR/+ACNHQmrqMS//FDgxiIKKm2g0ypVXXsnWrVsZPXp02HUkSZIkSUnC4aYkSZKk0ETze2FKCtx1F5xyClSrFlyuQvOHP/yBadOmsWDBAmrVqhV2HUmSJElSknC4KUmSJCk09Qpy8bnn5vvSugVuouIUjUb54osveOGFF2jevHnYdSRJkiRJScThpiRJkqTQdAQmBpxZCzgp4EwFZ+3atTRo0IAHHngg7CqSJEmSpCSUEnYBSZIkSaXXOXHIPBuIxCFXRbdx40bOOOMM/ud//ifsKpIkSZKkJOVwU5IkSVJoOgKnBJw5KuA8BWPPnj3069ePjh07cs0114RdR5IkSZKUpBxuSpIkSQrV7wLM6gGcEWCegpGXl8cll1xCTk4Ozz33HKmpqWFXkiRJkiQlKYebkiRJkkJ1ATAigJwKwD9wS9pE1bVrV6ZNm0aVKlXCriJJkiRJSmIONyVJkiSF7m9A1yLcXwZ4DmgSTB0F6I033uDAgQP85je/oWHDhmHXkSRJkiQlOYebkiRJkkJXCXiN2CrOgqoB/BvoF2gjBeHNN9/k/PPPZ/bs2WFXkSRJkiSVEA43JUmSJCWEKsA0YlvL1s7H9RHgQuB9oHcce6lw1q5dy6BBg7jtttu44ILCjK0lSZIkSfouh5uSJEmSEkYEuAL4mNg2sz8BmvLfczSrAD2A/wesAyYBdYq/pn7Anj176NOnD7169WLMmDFh15EkSZIklSBlwi4gSZIkSd9WFhh25AEQBfKA1NAaqSAqVqzI7bffzpAhQ4hEIj98gyRJkiRJ+eTKTUmSJEkJL4KDzWQQjUZ55JFH2L17NyNGjKB8+fJhV5IkSZIklTAONyVJkiRJgRg7diy/+c1v2LhxY9hVJEmSJEkllNvSSpIkSZKKbNq0adx8881MnjyZ1q1bh11HkiRJklRCuXJTkiRJklQkmzdv5qKLLuL++++nT58+YdeRJEmSJJVgrtyUJEmSJBVJ3bp1efnll+nevXvYVSRJkgptTzZs3gzZ2RAFqlSGunWhUuWwm0mSvs7hpiRJkiSpUPbv38/NN9/MHXfcwRlnnBF2HUmSpAI7dAiWZsKiRfDZZ0e/5vjjoXNnaNcOyqYXbz9J0ne5La0kSZIkqcDy8vK47LLLmDFjBikpvrSUJEnJ58MP4W+PwCuvHHuwCbHPvfIK/O1vsXskSeHyFagkSZIkqcDuuOMO3njjDV566SWqV68edh1JkqQCmT8f/vk07NqV/3t27YrdM39e/HpJkn6Y29JKkiRJkgpkxYoV3HfffcyYMYNmzZqFXUeSJKlAFi2CGa8V/v4ZMyAtDTp3Ca6TJCn/HG5KkiRJkgqkdevWrFmzhoYNG4ZdRZIkqUC2b4NXpxc959VXoWFDqHVc0bMkSQXjtrSSJEmSpHzZsGEDvXv3ZufOnQ42JUlSUnrlFcjNLXpObi68/HLRcyRJBedwU5IkSZL0g3bv3k2fPn1IT0+natWqYdeRJEkqsK1bYP364PI2bIhlSipZolE4fAgOHYRoXthtdDRuSytJkiRJ+l45OTkMGzaMsmXLMmHCBFJSfJ+sJElKPkuXBp+ZmQm9zgs+V1LxOrAfli6DtVmweTPs2xf7eFoa1KkDDRpCx45QvXqoNXWEw01JkiRJ0vd6++23Wb58OfPnz6dixYph15EkSSqUTZuCz/zkk+AzJRWf3FyYMwfmzoHDh7/7+cOHYePG2GPO29CmDZx3HlTwZVGoHG5KkiRJko4pNzeXnj17smrVKipVqhR2HUmSpELbujU5MiUVj9274PnnYys182v5cli3Di4cCg0bxq2afoB7CUmSJEmSjmrGjBl07tyZAwcOONiUJElJ79Ch+GRGo8HnSoqv7N3wxBMFG2x+ad8+mPDPYM/wVcE43JQkSZIkfcfKlSu58MILGTp0KOXKlQu7jiRJUpGVicM+hmXKQCQSfK6k+Inmwf/9H3zxReEzcnPhX5Ngz57gein/HG5KkiRJkr5h+/bt9O3blwEDBvCb3/wm7DqSJEmBqFUrOTIlxde778JHHxU9Z/9+eOXloueo4BxuSpIkSZK+Yd68eTRs2JBHH32UiEsRJElSCVGvfhwy6wWfKSl+cnNhzpzg8latgm3bgstT/jjclCRJkiQBEI1G2b17N/369WPmzJmkp6eHXUmSJCkwrVvHIbNN8JmS4mdtFmRnB5u5aFGwefphDjclSZIkSQDcd9999OzZk7y8PFJSfLkoSZJKloYN4bjjgsurVSuWKSl5fLg++MwNccjU9/PVqiRJkiSJF198kd/97nfce++9DjYlSVKJFIlA797B5fW+IJYpKXls2Rx85rZtcPhw8Lk6Nl+xSpIkSVIpt3jxYi655BLGjh3LueeeG3YdSZKkuGnYCLqeVvScrl2hUaOi50gqXnv2BJ8ZjcK+fcHn6tgcbkqSJElSKffxxx9z7bXXcs0114RdRZIkKe5+/GNo167w97drBz/2/WCSvsZF3MWrTNgFJEmSJEnh2Lt3L7t27WLgwIEMHDgw7DqSJEnFIiUF+veH2nVg1huQk5O/+8qUgbPOiq3ajLhsSEpKVarAzp3BZqakQIWKwWbq+znclCRJkqRSKC8vj0suuYR9+/bx2muvhV1HkiSpWEVS4LTTICMD5s2F5cuPfWZeWhq0aQPdfgQ1axZvT0nBqlsPPvoo2MzatWNvflDx8bdbkiRJkkqh2267jblz5/LOO++EXUWSJCk0NWtC335w7rmwcRNs/hSysyEKVK4M9erBCSdAuXJhN5UUhKZNYcH8YDObNAk2Tz/M4aYkSZIklTJPPPEEY8eOZdasWTRq1CjsOpIkSaFLLxcbejRtGnYTSfHUuBHUqAGffx5cZqfOwWUpf9wZXJIkSZJKmeOOO44nn3ySbt26hV1FkiRJkopNJAXOPDO4vI4doVq14PKUP67clCRJkqRSYt26dUQiEfr06RN2FUmSJEkKRes2sHIlrF5dtJwqVWJbWqv4uXJTkiRJkkqBnTt3csEFF3DfffeFXUWSJEmSQhOJQP8BULdu4TPKlYOLLoptaa3i53BTkiRJkkq4w4cPc+GFF1K1alXGjh0bdh1JkiRJClW5cnDpZdCsWcHvrVkTfvpTqF0n+F7KH7ellSRJkqQS7sYbbyQrK4uFCxdSvnz5sOtIkiRJUujKlYPhF8HSTJg9G3bv/v7ry5aFLl2gx5mQllYsFXUMDjclSZIkqYQbMmQIV111FXXq+NZiSZIkSfpSJALtO0DbtpCVBVlrYfOnsGsXRKNQsWJs+9oGDaBNG7ehTRQONyVJkiSphJo5cyb169enZ8+eYVeRJEmSpISVkgrNW8QeSnyeuSlJkiRJJdCyZcsYNGgQM2fODLuKJEmSJEmBcbgpSZIkSSXMli1b6Nu3L8OGDeP6668Pu44kSZIkSYFxW1pJkiRJKkGi0SjDhw+nSZMmPPLII0QikbArSZKkgB08AMtXwIb1sGUL7N0b+3i1arGz4Zo1g5NPjm2zKElSSeNwU5IkSZJKkEgkwv3330+TJk0oW7Zs2HUkSVKAcg7DW2/BwoVw6NB3P79lS+yxZAlUrgw9e0L7DuB7nSRJJYnDTUmSJEkqIcaOHUv37t3p0qVL2FUkSVLAtn0GkybB9u35uz47G6ZOhZUrYdBgKF8+vv0kSSounrkpSZIkSSXAc889x80330x2dnbYVSRJUsC2boUnnsj/YPPrPvgAnn4KDuwPvpckSWFwuClJkiRJCSgPyAJeB2YA7wEHj3HtggUL+OlPf8rf//53zjzzzGJqKEmSisPBg/D8c7C/CMPJLVtg8mSIRoPrJUlSWBxuSpIkSVKCiAJvA8OB6sDJwI+BXkAnoDLQA3iG/w46c3JyGDFiBNdffz0jR44s/tKSJCmuXp8JX3xR9JysLFi2tOg5kiSFzTM3JUmSJCkBfAJcBbzyPdccBv5z5DEGeALoXqYMr776Kg0bNox7R0mSVLx27YLFi4PLe/NNaNsWIi55kSQlMb+NSZIkSVLI5gCt+f7B5rety83ljMsu4xcLF9KkSRNSU1Pj1E6SJIXlvcXBbiX7xRfwwbrg8iRJCoPDTUmSJEkK0bvAeUCBd5u76SaYMYO/1q3LQ8HXkiRJCeCDD4LPXBeHTEmSipPDTUmSJEkKyV5i52vuLeiN48fHHlOnwokn8msgwB3rJElSAsjNha1bg8/dvDn4TEmSipPDTUmSJEkKyV1AgXeGy86GO+6Ap5+GLl0AyAVGAnmBtpMkSWHaty824Aza7t3BZ0qSVJzKhF1AkiRJkkqjPcD4gt6UlweVK8Pq1VCt2jc+tRSYBZwTTD1JkhS2AM/a/EZsnHIlSSourtyUJEmSpBC8ABRo4cT27bGVmkuWfGew+aXHgygmSZISQvkKkBKHn95WqhR8piRJxcnhpiRJkiSFYG5BLj54EAYNgvLloWXLYDIlSVJCK1MGjjsu+Ny6dYPPlCSpODnclCRJkqQQLM3vhdEoXH01bNoEkydDevoxL90E7AiinCRJSgiNGschs1HwmZIkFSeHm5IkSZIUgi/ye+HmzbBgAUyblq/lG/nOlSRJCa9Tp2DzKlWCk5sHmylJUnFzuClJkiRJIUjL74X16sH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      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 576.0,
       "width": 923.0
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 画出示意图\n",
    "plt.figure(figsize=(16, 10))\n",
    "plt.scatter(X[:, 0], X[:, 1], c=y, s=100, cmap='cool')    # 样本\n",
    "plt.scatter(c[:, 0], c[:, 1], s=100, marker='^', c='k')   # 中心点\n",
    "plt.scatter(X_sample[0][0], X_sample[0][1], marker=\"x\", \n",
    "            s=100, cmap='cool')    # 待预测的点\n",
    "\n",
    "for i in neighbors[0]:\n",
    "    # 预测点与距离最近的 5 个样本的连线\n",
    "    plt.plot([X[i][0], X_sample[0][0]], [X[i][1], X_sample[0][1]], \n",
    "             'k--', linewidth=0.6);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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